Routine maintenance is an important critical task of production management. Currently, preventative maintenance, (hereinafter “PM”) is based on a time scale, equipment parameter controls or production output. However, different manufacturing processes perform different usage of components or parts disposed within automated fabrication equipment.
An existing PM method used to perform a PM task in a semiconductor or wafer fabrication facility is shown in FIG. 1. FIG. 1 illustrates a flowchart 10 depicting the PM method of an existing method well known in the PM art. Initially, a PM task is defined (step 12).
Typically, in semiconductor manufacturing plants, two different parameters are used to estimate attrition rates associated with pieces of fabrication equipment. As shown in FIG. 1, the first parameter is based on a time scale, such as 1 week PM or 1 month PM, or after a timed or a plurality of timed processing cycles performed within a piece of fabrication equipment. The second parameter is related to equipment manufacturing data such as equipment output measured according to processed wafer counts or to wafer thickness, or to data relating to the status of a piece of fabrication equipment.
It is difficult to track a piece of fabrication equipment's attrition or rate of wear, or to track an equipment's lifespan when the piece of fabrication equipment is used for several or multiple manufacturing processes. A piece of fabrication equipment's usage is tracked by either determining a time period necessary for replacement of certain parts (step 14), or by determining a piece of fabrication equipment's status (step 16).
The equipment's usage results are then tracked in a PM schedule database (step 18). The PM schedule database is then downloaded into a PM system (PMS), and is then checked against PM criteria to determine wear. Typically the PM criteria define when a PM task should be performed based on data supplied by the part's manufacturer associated with each part disposed within a piece of fabrication equipment. The PM criteria are used to check the physical wear of a part disposed within a piece of fabrication equipment (step 22). The PM criteria and associated PM task is manually entered into an equipment quality system (“EQS”) database (step 20), wherein the EQS is in further communication with the PM schedule database to track what PM operation is being performed. Finally, a PM task is executed in accordance with a PM schedule generated by the PM system (step 24).
However, the method as shown in FIG. 1 does not track part usage based on the actual or type use of a part disposed within a piece of fabrication equipment associated with a fabrication process, but instead tracks the overall use of the equipment independent of the part's actual use within the piece of fabrication equipment.
Additionally, the amount of time and frequency each of the parts are used varies according to the recipe being used during each fabrication process or operation. If each part's usage is not tracked according to actual use, then the actual wear of the part cannot be accurately determined.
Using the existing method of FIG. 1 to determine wear of a part disposed within a piece of fabrication equipment, wherein the piece of fabrication has a plurality of parts, and wherein each of the plurality of parts has an associated PM criteria, the PM criteria preferably measured in cycles or time, an accurate measure of the part's wear cannot be determined. For example, in a piece of fabrication equipment, two different operations or processes are performed that each use a different recipe, recipe A and recipe B, respectively. When the piece of fabrication equipment uses recipe A, then a part X, is used may experience T seconds of use, however, if recipe B is used, then part X may be used for 3 T seconds, three times T seconds. The criteria specified by the part X manufacturer may specify a lifetime for part X of 30 hours of use or Y cycles of use. The PM system must then measure the output of the piece of fabrication equipment using both recipe A and recipe B to statistically estimate the actual usage of part X, and thus when a PM needs to be performed on part X. The PM process as shown in FIG. 1 is not an accurate process because the overall output of the equipment is measured, and not the actual usage of part X. To determine actual wear of part X, an actual wear or fatigue inspection must be performed.
By using the existing PM method, such as the method shown in FIG. 1, material waste and supply, or a loss of the stability of a piece of fabrication equipment can also occur when equipment is unexpectedly damaged. To repair the damaged equipment, engineers may perform a premature replacement of parts or components that are normally scheduled to be replaced during a future PM task in accordance with the PM system. Once the prematurely replaced parts are installed, engineers must deviate from the existing PM schedule to estimate future material cost or to estimate an equipment's process quality resulting from use of the replaced parts. Generating an updated PM schedule using existing PM methods is an inexact and cumbersome task.
It is desirable to provide a PM system and method that eliminates the need to physically check for wear of a part disposed within a piece of fabrication equipment.
It is desirable to automatically monitor actual wear of each of plurality of parts disposed within a piece of equipment and to determine each part's actual use.
It is desirable to provide an accurate preventative maintenance schedule that can help automated or fabrication equipment perform more efficiently and produce a stable product yield.
It is desirable to provide a system to track part usage of each of the plurality of parts on a piece of equipment.
It is desirable to provide a system to increase a piece of fabrication equipment and the piece of fabrication equipment associated parts' utility value and to lower overall PM costs.
It is desirable to provide an accurate PM schedule that is adjusted dynamically in accordance with actual wear of a plurality parts disposed.